November 2016

The MANTIS project is concerned with predictive maintenance on the basis of big data streams from large (industrial) operations. At the end of the processing pipe line, planning suggestions for maintenance actions will be the result. Usually, maintenance is performed by human operators.

However, with current developments in machine learning, AI and robotics, it becomes interesting to see what type of ‘corrective actions’ in maintenance could be performed by industrial service robots.

In industrial production lines it is common to observe fairly short times between failure, especially in long chains. Whereas individual components are often designed to function extremely well, for instance under a regime of ‘zero-defect manufacturing’, the performance of the line as a whole may be disappointing. What is more, the actions performed by human operators to solve the problems may be very mundane and simple, such as removing dirt due to fouling or lubricating critical components. With the current advances in robot hardware and software technology, it becomes increasingly attractive to automate such maintenance actions. Whereas maintenance in the form of module- or part replacement are too difficult for current state-of-the-art robotics, cleaning and tidying is definitely possible.

With this application domain in mind, a laboratory setup was designed for quickly developing a robotic maintenance task for the purpose of demonstration by a master student team (Francesco Bidoia, Rik Timmers, Marc Groefsema) under guidance of a PhD student (Amir Shantia). We were able to realize a rapid configuration of our existing mobile robot platform to realize simple cleaning and tidying actions, similar to what is needed in basic industrial maintenance tasks. The demonstration involves speech control, navigational autonomy, work piece approach and dynamic reactivity to three object types, using tool switching. Objects are considered to be either a) untouchable, or b) removable by hand, or to consist, c) of small fragments (cf. ‘dirt’) that needs to be brushed away. In three weeks, a full demonstration could be developed by the student team, using a mobile robot with a single arm that was designed earlier, for Robocup@Home tasks:

The 1st CREMA/C2NET Industrial workshop will take place the 24th November at Orona Fundazioa facilities located in Hernani (Basque Country – Spain). The event, organised by CREMA and C2NET H2020 EU projects, is intended to present future trends of European Industry especially those related to digitalization technologies applied to manufacturing. High levels speakers from the Basque Government, the European Commission, and the Industry sector (ill give their expert vision.

Moreover, CREMA and C2NET will present findings generated in both projects highlighting their approaches to meet above challenges. Presentations and practical demonstrations will be made by partners of both projects to present innovative solutions based on digital platforms in the Cloud to boost collaboration among manufacturing companies. Advanced Cloud technologies and applications will be shown to allow manufacturing companies faster and more efficient decision making for a better use of their manufacturing assets. Different business models and exploitation strategies followed by both projects to bring their outcomes to the market will also be presented.

Some MANTIS partners such as MGEP, IKERLAN, TEKNIKER, MCC, FAGOR ARRASATE and GOIZPER will attend this event to know other EU projects approaches to deal with common research areas and to make new contacts for potential collaboration actions in the future.

This project has received funding from the ECSEL Joint Undertaking under grant agreement No 662189. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Finland, Denmark, Belgium, Netherlands, Portugal, Italy, Austria, United Kingdom, Hungary, Slovenia, Germany.